{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "sns.set(rc={\"figure.figsize\": (6, 6)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 调色板 ###\n",
    "* 颜色很重要\n",
    "* color_palette()能传入任何Matplotlib所支持的颜色\n",
    "* color_palette()不写参数则默认颜色\n",
    "* set_palette()设置所有图的颜色\n",
    "\n",
    "### 分类色板 ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+3pLYMAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2219bd8b4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "current_palette = sns.color_palette()\n",
    "sns.palplot(current_palette)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6个默认的颜色循环主题： deep, muted, pastel, bright, dark, colorblind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 圆形画板 ###\n",
    "\n",
    "当你有六个以上的分类要区分时，最简单的方法就是在一个圆形的颜色空间中画出均匀间隔的颜色(这样的色调会保持亮度和饱和度不变)。这是大多数的当他们需要使用比当前默认颜色循环中设置的颜色更多时的默认方案。\n",
    "\n",
    "最常用的方法是使用hls的颜色空间，这是RGB值的一个简单转换。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0feda20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"hls\", 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x221a043f400>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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y3bHjTOcXZKPBf9ZZZ2nu3LlavXq1Vq1ape7ubj388MO666670m4jkUgqkUiaLAtAARoe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\nVwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0435518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.normal(size=(20, 8)) + np.arange(8) / 2\n",
    "sns.boxplot(data=data,palette=sns.color_palette(\"hls\", 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "hls_palette()函数来控制颜色的亮度和饱和\n",
    "* l-亮度 lightness \n",
    "* s-饱和 saturation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAIQRgAAAYQQgAEAYAQgAEOYXrclwsTq5M6IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0510748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.hls_palette(8, l=.7, s=.9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYQQgAEAYAQgAEEYAAgCEEYAAAGG+A1QNagtJItv0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a05c7588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Paired\",8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  使用xkcd颜色来命名颜色 ###\n",
    "xkcd包含了一套众包努力的针对随机RGB色的命名。产生了954个可以随时通过xdcd_rgb字典中调用的命名颜色。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x221a06bb828>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iqUrtleK5P3Me5+aqrP9Iz/7l56o693HI55J85j7lE/FXq6io0Nq1a1VUVKS8vDzV1NR0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\nAADCIhYAAEBYxAIAAAiLWAAAAGH9f40iyD3Dkp/HAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a06046d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([0, 1], [0, 1], sns.xkcd_rgb[\"pale red\"], lw=3)\n",
    "plt.plot([0, 1], [0, 2], sns.xkcd_rgb[\"medium green\"], lw=3)\n",
    "plt.plot([0, 1], [0, 3], sns.xkcd_rgb[\"denim blue\"], lw=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAABhCAYAAAAa2uy9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a05b1588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\"windows blue\", \"amber\", \"greyish\", \"faded green\", \"dusty purple\"]\n",
    "sns.palplot(sns.xkcd_palette(colors))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  连续色板 ###\n",
    "色彩随数据变换，比如数据越来越重要则颜色越来越深"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n92XLlQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0874f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Blues\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果想要翻转渐变，可以在面板名称中添加一个_r后缀"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMgAE+A0o21lWLPwc+wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0718400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"BuGn_r\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  cubehelix_palette()调色板 ###  \n",
    "色调线性变换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0749f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"cubehelix\", 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a07183c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.cubehelix_palette(8, start=.5, rot=-.75))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAABhCAYAAABGShAtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a03d00f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.cubehelix_palette(8, start=.75, rot=-.150))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  light_palette() 和dark_palette()调用定制连续调色板  ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0617f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette(\"green\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEOAnIQdWAKtvuJAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a088fba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.dark_palette(\"purple\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAAPYQAAD2EBqD+naQAAAshJREFUeJzt3DFKmwEYxvE3JYOggw0ujikV3IReQXDzAl7BC3iEXMBj\ndHLuFSpOZmqcTAWrVpQKCXydHLpUbZXv+fT3W7J8hId3yB8SSK9pmqYAgFa9a3sAACDIABBBkAEg\ngCADQABBBoAAggwAAQQZAAIIMgAEEGQACPDoIPtDLwD4N6enDz/Tf+yb9Xq92tn5XOPx+f9selO2\ntj7WaLRZe3tfajK5antOJwyHyzUabdb+/teaTm/antMZq6tLtbv7qQ4OvtXFxV3bczphMFio7e0P\ndXR0Wbe387bndMbiYr82Nt7X5WXV3Nme1aODXFU1Hp/X4eH3l9ry6qytrVRV1WRyVcfHP1pe0y3T\n6U2dnPxse0bnXFzc1dnZr7ZndMrt7byur2dtz+ic+bxq5mzPym/IABBAkAEggCADQABBBoAAggwA\nAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAQQZAAIIMgAEEGQACCDIABBAkAEggCAD\nQABBBoAAggwAAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAQQZAAIIMgAEEGQACCDI\nABBAkAEggCADQABBBoAAggwAAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAQQZAAII\nMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAA\nggwAAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAQQZAAIIMgAEEGQACCDIABCg/5SH\n19dXXmrHqzQcLv/xysPub7W6utTykm65v9dgsNDyku64v9Xi4pM+Bt+8+3v1ne1JZrOHn+k1TdO8\n/BQA4G98ZQ0AAQQZAAIIMgAEEGQACCDIABBAkAEggCADQABBBoAAggwAAX4DAPhTTdKF2ucAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0552630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette(\"navy\", reverse=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\numpy\\ma\\core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.minimum.reduce will be axis=0, not the current None, to match np.minimum.reduce. Explicitly pass 0 or None to silence this warning.\n",
      "  return self.reduce(a)\n",
      "C:\\Anaconda3\\lib\\site-packages\\numpy\\ma\\core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.maximum.reduce will be axis=0, not the current None, to match np.maximum.reduce. Explicitly pass 0 or None to silence this warning.\n",
      "  return self.reduce(a)\n"
     ]
    },
    {
     "data": {
      "image/png": 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zD68dmVEQhLJXqj2u/Prrr9y/f5/du3cXeh0tLQlaWhWnsZC2tlaB/6oTb+89REVFAvDJ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f+p9y/unITtZs/x6AIR8MpXlDd530t3v/Dk6di8Taypoxw8fp9d56enoaAQGfcuvWX6hUKmbO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a0f416a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = np.random.multivariate_normal([0, 0], [[1, -.5], [-.5, 1]], size=300).T\n",
    "pal = sns.dark_palette(\"green\", as_cmap=True)\n",
    "sns.kdeplot(x, y, cmap=pal);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAABhCAYAAAAHpNImAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x221a05b3c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette((210, 90, 60), input=\"husl\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
